A torque distribution method and device, electronic equipment and storage medium

Abstract

The application provides a torque distribution method and device, electronic equipment and storage medium, and relates to the technical field of vehicles.The torque distribution method comprises the following steps: determining a traction force loss index and a stability deviation index according to vehicle operating state information; generating a dynamic weight factor according to the traction force loss index and the stability deviation index; weighting and fusing a virtual differential lock torque distribution amount and a torque vector distribution amount according to the dynamic weight factor to determine a target torque increment of each wheel; generating a torque instruction according to a basic driving torque and the target torque increment; and sending the torque instruction to a driving motor corresponding to each wheel for execution.The application can adaptively adjust the control focus according to the current working condition of the vehicle, preferentially restores the traction force in the slipping working condition, preferentially corrects the vehicle attitude in the instability working condition, and thus improves the driving smoothness and the control stability of the vehicle on the low adhesion road surface.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and more specifically, to a torque distribution method, apparatus, electronic device, and storage medium. Background Technology

[0002] With the development of new energy vehicle technology, especially the gradual application of four-wheel independent drive electric vehicles, vehicle dynamics control systems are evolving from traditional centralized drive architecture to distributed drive architecture. Distributed drive electric vehicles, by independently configuring drive motors for each wheel, enable the vehicle to quickly and accurately adjust the driving force of each wheel, providing a new technical foundation for improving the vehicle's power and stability under complex working conditions. However, under low-friction road surface conditions (such as ice, snow, wet and slippery roads), vehicle tires are prone to slippage, resulting in a decrease in traction and a deterioration in driving stability.

[0003] To address the aforementioned issues, relevant technologies typically employ electronic stability control systems and traction control systems for intervention. The basic principle is to restore traction and vehicle stability by applying braking to the slipping wheel or limiting the driving torque when wheel slippage or vehicle instability is detected. However, this approach has low energy utilization efficiency, limited control response speed, poor smoothness, and dispersed and insufficiently coordinated control strategies. Summary of the Invention

[0004] The problem addressed by this invention is how to improve the handling, safety, and energy efficiency of vehicles on low-friction surfaces.

[0005] To address the above problems, the present invention provides a torque distribution method, apparatus, electronic device, and storage medium.

[0006] In a first aspect, the present invention provides a torque distribution method, comprising: The traction loss index and stability deviation index are determined based on vehicle operating status information. Dynamic weighting factors are generated based on the traction loss index and the stability deviation index. The virtual differential lock torque distribution amount and torque vector distribution amount are weighted and fused according to the dynamic weighting factor to determine the target torque increment of each wheel. A torque command is generated based on the basic drive torque and the target torque increment, and the torque command is sent to the drive motor corresponding to each wheel for execution.

[0007] Optionally, determining the traction loss index and stability deviation index based on vehicle operating status information includes: Determine the slip ratio of each wheel and the deviation of the vehicle's yaw rate based on the vehicle's operating status information; The traction loss index is determined based on the slip ratio; The stability deviation index is determined based on the yaw rate deviation.

[0008] Optionally, generating dynamic weighting factors based on the traction loss index and the stability deviation index includes: A two-dimensional mapping relationship is constructed based on the traction loss index and the stability deviation index; The dynamic weighting factor is obtained by interpolating the traction loss index and the stability deviation index based on the two-dimensional mapping relationship. The dynamic weighting factor increases when the traction loss index increases and decreases when the stability deviation index increases.

[0009] Optionally, the weighted fusion of the virtual differential lock torque distribution and torque vector distribution based on the dynamic weighting factor includes: The virtual differential lock torque distribution is determined based on the slip ratio of each wheel and its deviation from the target slip ratio; The torque vector distribution is determined based on the vehicle's yaw rate deviation. The virtual differential lock torque distribution is weighted according to the dynamic weighting factor, and the torque vector distribution is complementary weighted. The target torque increment of each wheel is determined based on the weighted virtual differential lock torque distribution and torque vector distribution.

[0010] Optionally, determining the virtual differential lock torque distribution based on the slip ratio of each wheel and its deviation from the target slip ratio includes: Wheels with a slip ratio greater than a preset threshold are identified as slipping wheels, and the slip ratio deviation between the slip ratio of the slipping wheel and the target slip ratio is determined. The torque reduction amount of each slipping wheel is determined based on the slip ratio deviation, and the torque reduction amount is redistributed according to the adhesion ability of the non-slipping wheels to determine the virtual differential lock torque distribution amount of each wheel.

[0011] Optionally, determining the torque vector distribution based on the vehicle yaw rate deviation includes: The target yaw moment is determined based on the deviation between the vehicle's desired yaw rate and the actual yaw rate. The target yaw moment is distributed to each wheel according to a preset distribution rule to obtain the torque vector distribution of each wheel.

[0012] Optionally, generating the torque command based on the base drive torque and the target torque increment includes: The target torque increment is superimposed with the base drive torque to generate the initial command; The initial command is constrained based on the torque output capability of the drive motor to generate the torque command.

[0013] In a second aspect, the present invention provides a torque distribution device, comprising: The first module is used to determine the traction loss index and stability deviation index based on vehicle operating status information; The second module is used to generate dynamic weighting factors based on the traction loss index and the stability deviation index. The third module is used to perform weighted fusion of the virtual differential lock torque distribution amount and the torque vector distribution amount according to the dynamic weighting factor to determine the target torque increment of each wheel, generate a torque command based on the basic drive torque and the target torque increment, and send the torque command to the drive motor corresponding to each wheel for execution.

[0014] Thirdly, the present invention provides an electronic device, including a memory and a processor; The memory is used to store computer programs; The processor is configured to implement the torque distribution method as described in the first aspect when executing the computer program.

[0015] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the torque distribution method as described in the first aspect.

[0016] The beneficial effects of the torque distribution method of the present invention are as follows: dynamic weighting factors are generated based on the traction loss index and stability deviation index, and the torque distribution amount of the virtual differential lock and the torque vector distribution amount are weighted and fused based on the dynamic weighting factors, thereby realizing the unified coordination of traction control and vehicle stability control. It can adaptively adjust the control focus according to the current operating conditions of the vehicle, prioritizing the recovery of traction under slipping conditions and prioritizing the correction of vehicle attitude under unstable conditions, thereby avoiding the discontinuity problems caused by conflicting control targets and frequent switching, effectively reducing energy dissipation, improving the overall vehicle energy efficiency, and improving the driving smoothness and handling stability of the vehicle on low-adhesion road surfaces. Attached Figure Description

[0017] Figure 1 This is a schematic flowchart of the torque distribution method according to an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the principle of the torque distribution method according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the process for determining the traction loss index and stability deviation index according to an embodiment of the present invention; Figure 4This is a schematic diagram of the process for generating dynamic weighting factors according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the weighted fusion process according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the process for determining the virtual differential lock torque distribution in an embodiment of the present invention; Figure 7 This is a schematic diagram of the process for determining the torque vector allocation amount according to an embodiment of the present invention; Figure 8 This is a schematic diagram of the process for generating torque commands according to an embodiment of the present invention; Figure 9 This is a system architecture diagram of the torque distribution device according to an embodiment of the present invention; Figure 10 This is a system architecture diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0018] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the accompanying drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0019] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0020] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to"; the term "based on" means "at least partially based on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; and the term "optionally" means "optional embodiments". Definitions of other terms will be given in the following description. It should be noted that the concepts of "first," "second," etc., mentioned in this invention are used only to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0021] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0022] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0023] like Figure 1 As shown, an embodiment of the present invention provides a torque distribution method, comprising: S100: Determine the traction loss index and stability deviation index based on vehicle operating status information.

[0024] Specifically, in combination Figure 2 As shown, the following vehicle operating status information can be obtained through vehicle sensors: steering wheel angle δ, and wheel speeds ω. i (i = fl, fr, rl, rr, i.e., left front wheel, right front wheel, left rear wheel, right rear wheel), yaw rate γ, longitudinal / lateral acceleration a x a y First, the longitudinal vehicle speed V is estimated based on the weighted average of the wheel speeds of the wheels that are not slipping. x The system incorporates inertial sensor data for correction to ensure reliable vehicle speed references even on low-friction surfaces; then, it calculates the slip ratio λ for each wheel. i = (ω i * R - V x ) / max(V x ω i * R), where R is the tire rolling radius; then, using a simplified inverse model of the tire model (such as the magic formula), combined with wheel speed, torque, and vehicle acceleration, the maximum usable adhesion coefficient μ of each tire contact surface is estimated in real time. est_i Finally, the desired yaw rate γ is calculated. des = min( (V x *δ) / (L+K us * V x ^2),μ est * g / V x L represents wheelbase, K us The steering characteristic coefficient is represented here. A dual limiter is introduced. The first is the steady-state value determined by the vehicle geometry and dynamics, and the second is the physical limit value based on the adhesion coefficient (g is the acceleration due to gravity). On low-adhesion surfaces, the second limiter plays a dominant role and automatically provides a safe and conservative stability target. After estimating the above key state parameters, the traction loss index and stability deviation index are constructed.

[0025] An exemplary process for estimating the road surface adhesion coefficient is as follows: (1) Calculate the longitudinal force (F) x ): F x,ij ≈ ; Among them, T ij The torque acting on the wheel is represented by N*m (positive for driving and negative for braking); r represents the tire rolling radius, in meters.

[0026] (2) Calculate the vertical load (F) z Taking a single wheel as an example: ; ; Where m represents the total vehicle mass, in kg; a x The values ​​represent the longitudinal acceleration sensor readings in m / s²; h represents the center of mass height in m; L represents the wheelbase in m; and a and b represent the distances from the center of mass to the front and rear axles in m.

[0027] (3) Calculate the adhesion coefficient: μ est_i = ; (4) Estimate the maximum usable adhesion coefficient: μ est_max =K*μ est_i Wherein, K is the peak factor (usually taken as 1.0~1.1, which can be obtained by fitting data from the OEM database).

[0028] S200: Generate dynamic weighting factors based on the traction loss index and the stability deviation index.

[0029] Specifically, the traction loss index and stability deviation index are input into a preset two-dimensional lookup table or interpolation function to obtain dynamic weighting factors.

[0030] S300: The virtual differential lock torque distribution amount and torque vector distribution amount are weighted and fused according to the dynamic weighting factor to determine the target torque increment of each wheel. A torque command is generated according to the basic drive torque and the target torque increment, and the torque command is sent to the drive motor corresponding to each wheel for execution.

[0031] Specifically, the virtual differential lock torque distribution ΔT is calculated separately. vdl_i and torque vector distribution ΔT tvc_i , Based on the dynamic weighting factor α, the two are fused to obtain the target torque increment ΔT. final_iThe target torque increment ΔT final_i With basic drive torque T base_i The initial commands for each wheel are superimposed to obtain the initial commands. The motor output capacity of the initial commands is constrained to obtain the final torque commands, which are then sent to the motor controllers of each wheel for execution.

[0032] In this embodiment, a dynamic weighting factor is generated based on the traction loss index and the stability deviation index. The virtual differential lock torque distribution and torque vector distribution are then weighted and fused based on the dynamic weighting factor, achieving unified coordination between traction control and vehicle stability control. This allows for adaptive adjustment of the control focus according to the vehicle's current operating conditions, prioritizing traction recovery in slippage conditions and correcting vehicle attitude in instability conditions. This avoids conflicts in control objectives and discontinuities caused by frequent switching, effectively reduces energy dissipation, improves overall vehicle energy efficiency, and enhances the vehicle's ride comfort and handling stability on low-adhesion surfaces.

[0033] Optionally, determining the traction loss index and stability deviation index based on vehicle operating status information includes: S110: Determine the slip ratio of each wheel and the deviation of the vehicle's yaw rate based on the vehicle's operating status information.

[0034] Specifically, in combination Figure 3 As shown, the slip ratio of each wheel is calculated based on the estimated wheel speed and vehicle speed of the four wheels, and wheels with abnormal slip ratios are screened out. The expected yaw rate is calculated through the vehicle dynamics model, thereby determining the deviation between the expected yaw rate and the actual yaw rate.

[0035] S120: Determine the traction loss index based on the slip ratio.

[0036] Specifically, the traction loss index can be expressed as: I T = f(max(λ i ), number of slipping wheels, μ est_i (differences); It could be a single wheel slipping severely, or a significant difference in adhesion between the two wheels.

[0037] S130: Determine the stability deviation index based on the yaw rate deviation.

[0038] Specifically, the stability deviation index can be expressed as: I S = f(|γ des -γ actual | Lateral acceleration a y Steering wheel angle change rate dδ / dt); For the stability deviation index, the larger the deviation and the faster the change, the higher the index.

[0039] In this optional embodiment, the traction loss index is determined based on the wheel slip ratio, and the stability deviation index is determined based on the yaw rate deviation. This enables the control system to directly use key physical quantities that reflect the longitudinal adhesion state of the tires and the dynamic characteristics of the vehicle's yaw to quantitatively evaluate the vehicle's operating conditions. It can accurately identify the degree of wheel slippage and the degree of vehicle stability deviation, thereby providing a reliable basis for subsequent control decisions and improving the control system's adaptability and response accuracy to complex low-adhesion road conditions.

[0040] Optionally, generating dynamic weighting factors based on the traction loss index and the stability deviation index includes: S210: Construct a two-dimensional mapping relationship based on the traction loss index and the stability deviation index.

[0041] Specifically, in combination Figure 4 As shown, a two-dimensional lookup table model is constructed, with the traction loss index and stability deviation index as input axes. The lookup data can be obtained through simulation or real vehicle calibration, for example:

[0042] S220: Based on the two-dimensional mapping relationship, interpolate the traction loss index and the stability deviation index to obtain the dynamic weighting factor, wherein the dynamic weighting factor increases when the traction loss index increases, and decreases when the stability deviation index increases.

[0043] Specifically, the dynamic weighting factor α is calculated using the bilinear interpolation method to ensure output continuity. When the traction loss index is large and the stability deviation index is small, α approaches 1. When the stability deviation index is large and the traction loss index is small, α approaches 0. When both are large, α takes an intermediate value (such as 0.3~0.7).

[0044] To avoid jitter, the dynamic weighting factor α can also be subjected to a first-order low-pass filter.

[0045] In this optional embodiment, a two-dimensional mapping relationship between the traction loss index and the stability deviation index is constructed, and a dynamic weighting factor is generated by interpolation calculation. This allows the control weight to change continuously with the vehicle state, achieving a smooth transition. This avoids the torque jump problem caused by abrupt changes in the control mode, significantly improving the continuity and smoothness of the control process. It also achieves adaptive allocation of control objectives, effectively balancing the ability to get out of trouble and the stability of handling.

[0046] Optionally, the weighted fusion of the virtual differential lock torque distribution and torque vector distribution based on the dynamic weighting factor includes: S310: Determine the virtual differential lock torque distribution based on the slip ratio of each wheel and its deviation from the target slip ratio.

[0047] Specifically, in combination Figure 5 As shown, the virtual differential lock torque distribution is calculated based on the deviation between the slip ratio of each wheel and the target slip ratio.

[0048] S320: Determine the torque vector distribution based on the vehicle's yaw rate deviation.

[0049] Specifically, the torque vector distribution is calculated based on the deviation between the vehicle's desired yaw rate and the actual yaw rate.

[0050] S330: The virtual differential lock torque distribution is weighted according to the dynamic weighting factor, and the torque vector distribution is complementary weighted. The target torque increment of each wheel is determined based on the weighted virtual differential lock torque distribution and torque vector distribution.

[0051] Specifically, an exemplary target torque increment can be expressed as: ΔT final_i = α·ΔT vdl_i + (1 α)·ΔT tvc_i ; In this optional embodiment, the virtual differential lock torque distribution amount is determined based on the slip ratio deviation and the torque vector distribution amount is determined based on the yaw rate deviation, respectively. The two types of control quantities are then weighted and fused using dynamic weighting factors, so that they work together under a unified framework. This allows for the reasonable distribution of driving force among the wheels while keeping the total driving force basically unchanged, and at the same time generates the required yaw moment. This balances the vehicle's off-road performance and steering stability under complex conditions on low-adhesion road surfaces, thereby improving the overall dynamic performance of the vehicle.

[0052] Optionally, determining the virtual differential lock torque distribution based on the slip ratio of each wheel and its deviation from the target slip ratio includes: S311: Identify wheels with a slip ratio greater than a preset threshold as slipping wheels, and determine the slip ratio deviation between the slip ratio of the slipping wheel and the target slip ratio.

[0053] Specifically, in combination Figure 6 As shown, the torque distribution of the virtual differential lock can be determined based on the virtual differential lock module. The goal of the virtual differential lock module is to minimize the slip ratio of the drive wheels while keeping the total drive torque constant. The virtual differential lock module first identifies the set S of slipping wheels. slipFor each slipping wheel j∈S slip According to its slip ratio λ j The torque reduction ΔT is calculated by the PD controller. reduce_j The specific calculation method is as follows: the control variable is the slip ratio λ of the slipping wheel j. j Expected slip ratio (λ) des The target slip ratio (λ) is a dynamic value based on road adhesion estimation. On low-adhesion surfaces (such as ice and snow), the slip ratio corresponding to the maximum adhesion coefficient is typically very small (e.g., 0.05-0.12). Therefore, during simulation or real-vehicle calibration, a target slip ratio slightly lower than this is set, for example, λ. des = 0.08, to ensure stability and retain a certain lateral force margin; control error (e j ):e j(t) =λ j(t) -λ des When the actual slip ratio is greater than the expected value, the error is positive, which means that the driving torque needs to be reduced.

[0054] The calculation formula for the PD controller is as follows: ΔT reduce_j(t) = K p * e j(t) + K d * [de j(t) / dt]; For the proportional term K p * e j(t) K p It is the proportional gain, which determines the strength of the controller's response to the current slip error. If the slip ratio λ_j is significantly higher than the target value λ, then... des (e) j (Very large), this term will generate a large, proportional torque reduction command, quickly curbing the slippage trend. This is the main force of the control response; for the differential term K... d * [de j(t) / dt]:K d It is the differential gain, de j(t) / dt is the rate of change of the slip ratio error (i.e., the speed at which slip intensifies), used for prediction and damping terms; if the slip ratio is rising rapidly (de j / dt is a large positive value), even if the current error e j It's not too big yet; the derivative term will also generate an additional torque reduction command in advance to prevent severe overshoot and oscillation in the system. This is like an experienced driver releasing the accelerator the moment they feel the wheels start to spin freely; if the slip ratio has already begun to decrease (de j / dt is negative), the derivative term will become a negative value (equivalent to reducing the amount of braking), preventing excessive braking and helping torque to recover smoothly; Kp and K d It is not a fixed value, but can be determined based on the road surface adhesion coefficient (μ). est Adjustments can be made in real time.

[0055] S312: Determine the torque reduction amount of each slipping wheel based on the slip ratio deviation, and redistribute the torque reduction amount according to the adhesion ability of the non-slipping wheels to determine the virtual differential lock torque distribution amount of each wheel.

[0056] Specifically, ΣΔT reduce_j The adhesion potential is assigned according to the weight of each non-slipping wheel, where the adhesion potential weight is W. i It is proportional to its estimated adhesion coefficient μ est_i ; For non-pulling wheels: ΔT vdl_i (Non-pulling wheel) = (ΣΔT) reduce_j ) * (W i / ΣW non-slip ); The above formula can be used to calculate how much torque should be added to each non-slipping wheel to achieve torque transfer from the slipping side to the non-slipping side, W. i This represents the adhesion potential weight of the currently being calculated non-slipping wheel i, and this weight is proportional to the estimated adhesion coefficient μ of the ground where the wheel is located. est_i The higher the adhesion coefficient, the better. i The larger the value, the more driving torque the wheel can safely withstand without slipping; ΣW non-slip W represents the sum of the adhesion potential weights of all non-slipping wheels; i / ΣW non-slip The physical meaning of ) is the proportion of torque-carrying capacity of wheel i among all available (non-slipping) wheels; For slippery wheels: ΔT vdl_i (pulling the wheel) = -ΔT reduce_i ; The effect of torque redistribution is that power is pumped from the low-traction side to the high-traction side, just like an electronic pump, which is extremely efficient.

[0057] In this optional embodiment, by identifying slipping wheels and determining the torque reduction based on slip ratio deviation, and redistributing the reduced torque according to the adhesion of the non-slipping wheels, the driving force is efficiently transferred from low-adhesion wheels to high-adhesion wheels, avoiding the problem of energy dissipation in the form of heat, improving energy utilization efficiency, and making the driving force preferentially distributed to wheels with higher adhesion potential, thereby improving the vehicle's traction and off-road performance on low-adhesion surfaces.

[0058] Optionally, determining the torque vector distribution based on the vehicle yaw rate deviation includes: S321: Determine the target yaw moment based on the deviation between the vehicle's desired yaw rate and the actual yaw rate.

[0059] Specifically, in combination Figure 7 As shown, the torque vector distribution can be determined based on the active torque vector module, the goal of which is to generate a compensating yaw moment ΔM. z This allows the actual yaw rate to track the desired value; the active torque vector module first calculates the required yaw torque: ΔM z = K p *e γ +K d * de γ / dt +K i *∫e γ dt; Wherein, the PID parameters are based on μ est Adaptive adjustment (at low attachment, K) d Enhancement to suppress overshoot, K i (To reduce the risk of PID saturation), the specific values ​​are determined by the optimal combination based on the actual vehicle calibration. Different driving modes will have different corresponding PID values.

[0060] S322: Distribute the target yaw moment to each wheel according to a preset distribution rule to obtain the torque vector distribution of each wheel.

[0061] Specifically, torque distribution optimization will ΔM z The wheels are allocated diagonally. ΔT tvc_fl = +k *ΔM z ; ΔT tvc_fr = -k *ΔM z ; ΔT tvc_rl = +k *ΔM z ; ΔT tvc_rr = -k *ΔM z ; Where k is a coefficient related to the wheel track and tire radius.

[0062] In this optional embodiment, the target yaw moment is calculated based on the yaw rate deviation and distributed to each wheel according to a preset distribution rule, thereby realizing the active adjustment of the vehicle's yaw motion. This not only results in a faster response speed but also avoids the impact of braking, improving the vehicle's handling stability and ride comfort under cornering conditions, and effectively suppressing understeer or oversteer.

[0063] Optionally, generating the torque command based on the base drive torque and the target torque increment includes: S340: The target torque increment is superimposed with the basic drive torque to generate an initial command.

[0064] Specifically, in combination Figure 8 As shown, the target torque increment ΔT final_i With basic drive torque T base_i By superimposing these, the initial instructions are obtained.

[0065] S350: Constrain the initial command according to the torque output capability of the drive motor to generate the torque command.

[0066] Specifically, the initial command is limited based on the maximum output torque of the drive motor. If it exceeds the peak torque, it is scaled proportionally to generate the final torque command.

[0067] If a slight slippage is caused by factors such as road surface micro-irregularities or changes in tire dynamic characteristics, the slip ratio PID fine-tuner can monitor the slip ratio of the wheel in real time. If it deviates from the preset optimal slip range (e.g., 0.05-0.15), the fine-tuner will generate a small torque correction amount, which is directly added to the torque command to ensure that the tire always works near the optimal adhesion zone, thereby greatly enhancing the robustness and adaptability of the entire upper-level control system.

[0068] In this optional embodiment, the initial command is generated by superimposing the target torque increment with the basic drive torque, and the torque command is constrained by combining the output capability of the drive motor. This ensures that the control command is executed within the physical capability range of the motor, thereby improving the safety and reliability of the system operation. It also facilitates the realization of high-bandwidth, fast-response torque control and improves the engineering feasibility and robustness of the vehicle control system.

[0069] like Figure 9 As shown, an embodiment of the present invention provides a torque distribution device 900, comprising: The first module 910 is used to determine the traction loss index and stability deviation index based on vehicle operating status information; The second module 920 is used to generate dynamic weighting factors based on the traction loss index and the stability deviation index. The third module 930 is used to perform weighted fusion of the virtual differential lock torque distribution amount and the torque vector distribution amount according to the dynamic weighting factor to determine the target torque increment of each wheel, generate a torque command according to the basic drive torque and the target torque increment, and send the torque command to the drive motor corresponding to each wheel for execution.

[0070] like Figure 10 As shown, an electronic device 1000 provided in this embodiment of the invention includes a memory 1020 and a processor 1010; the memory 1020 is used to store a computer program; the processor 1010 is used to implement the torque distribution method as described above when the computer program is executed.

[0071] Alternatively, an electronic device 1000 includes a memory 1020 and a processor 1010 coupled to the memory 1020; the memory 1020 is configured to store a computer program; the processor 1010 is configured to perform the following operations when the computer program is executed: The traction loss index and stability deviation index are determined based on vehicle operating status information. Dynamic weighting factors are generated based on the traction loss index and the stability deviation index. The virtual differential lock torque distribution amount and torque vector distribution amount are weighted and fused according to the dynamic weighting factor to determine the target torque increment of each wheel. A torque command is generated based on the basic drive torque and the target torque increment, and the torque command is sent to the drive motor corresponding to each wheel for execution.

[0072] This invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the torque distribution method described above.

[0073] Alternatively, a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the following operations: The traction loss index and stability deviation index are determined based on vehicle operating status information. Dynamic weighting factors are generated based on the traction loss index and the stability deviation index. The virtual differential lock torque distribution amount and torque vector distribution amount are weighted and fused according to the dynamic weighting factor to determine the target torque increment of each wheel. A torque command is generated based on the basic drive torque and the target torque increment, and the torque command is sent to the drive motor corresponding to each wheel for execution.

[0074] The present invention will now be described an electronic device 1000 that can serve as a server or client of the present invention, which is an example of a hardware device that can be applied to various aspects of the present invention. The electronic device 1000 is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device 1000 can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0075] Electronic device 1000 includes a computing unit that can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) or a computer program loaded from a storage unit into random access memory (RAM). The RAM may also store various programs and data required for device operation. The computing unit, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0076] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc. In this application, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of the present invention according to actual needs. Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units can be implemented in hardware or as software functional units.

[0077] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A torque distribution method, characterized in that, include: The traction loss index and stability deviation index are determined based on vehicle operating status information; Dynamic weighting factors are generated based on the traction loss index and the stability deviation index. The virtual differential lock torque allocation and torque vector allocation are weighted and fused according to the dynamic weighting factor to determine the target torque increment for each wheel. A torque command is generated based on the base drive torque and the target torque increment, and the torque command is sent to the drive motor corresponding to each wheel for execution. The weighted fusion of the virtual differential lock torque allocation and torque vector allocation according to the dynamic weighting factor includes: determining the virtual differential lock torque allocation based on the slip ratio of each wheel and its deviation from the target slip ratio. Specifically, this includes: identifying wheels with slip ratios greater than a preset threshold as slipping wheels, determining the slip ratio deviation between the slipping wheel and the target slip ratio; determining the torque reduction amount for each slipping wheel based on the slip ratio deviation, and redistributing the torque reduction amount based on the adhesion capability of the non-slipping wheels to determine the virtual differential lock torque allocation for each wheel, so as to determine the target torque increment for each wheel based on the weighted virtual differential lock torque allocation and torque vector allocation.

2. The torque distribution method according to claim 1, characterized in that, The determination of the traction loss index and stability deviation index based on vehicle operating status information includes: Determine the slip ratio of each wheel and the deviation of the vehicle's yaw rate based on the vehicle's operating status information; The traction loss index is determined based on the slip ratio; The stability deviation index is determined based on the yaw rate deviation.

3. The torque distribution method according to claim 1, characterized in that, The process of generating dynamic weighting factors based on the traction loss index and the stability deviation index includes: A two-dimensional mapping relationship is constructed based on the traction loss index and the stability deviation index; The dynamic weighting factor is obtained by interpolating the traction loss index and the stability deviation index based on the two-dimensional mapping relationship. The dynamic weighting factor increases when the traction loss index increases and decreases when the stability deviation index increases.

4. The torque distribution method according to claim 1, characterized in that, The weighted fusion of the virtual differential lock torque distribution and torque vector distribution based on the dynamic weighting factor further includes: The torque vector distribution is determined based on the vehicle's yaw rate deviation. The virtual differential lock torque distribution is weighted according to the dynamic weighting factor, and the torque vector distribution is complementary weighted. The target torque increment of each wheel is determined based on the weighted virtual differential lock torque distribution and torque vector distribution.

5. The torque distribution method according to claim 4, characterized in that, The determination of torque vector distribution based on vehicle yaw rate deviation includes: The target yaw moment is determined based on the deviation between the vehicle's desired yaw rate and the actual yaw rate. The target yaw moment is distributed to each wheel according to a preset distribution rule to obtain the torque vector distribution of each wheel.

6. The torque distribution method according to claim 1, characterized in that, The process of generating torque commands based on the base drive torque and the target torque increment includes: The target torque increment is superimposed with the base drive torque to generate the initial command; The initial command is constrained based on the torque output capability of the drive motor to generate the torque command.

7. A torque distribution device, characterized in that, include: The first module is used to determine the traction loss index and stability deviation index based on vehicle operating status information; The second module is used to generate dynamic weighting factors based on the traction loss index and the stability deviation index. The third module is used to perform weighted fusion of the virtual differential lock torque allocation and torque vector allocation based on the dynamic weighting factor to determine the target torque increment for each wheel, generate a torque command based on the base drive torque and the target torque increment, and send the torque command to the drive motor corresponding to each wheel for execution. The weighted fusion of the virtual differential lock torque allocation and torque vector allocation based on the dynamic weighting factor includes: determining the virtual differential lock torque allocation based on the slip ratio of each wheel and its deviation from the target slip ratio; specifically, identifying wheels with slip ratios greater than a preset threshold as slipping wheels, determining the slip ratio deviation between the slipping wheel's slip ratio and the target slip ratio; determining the torque reduction amount for each slipping wheel based on the slip ratio deviation, and redistributing the torque reduction amount based on the adhesion capability of the non-slipping wheels to determine the virtual differential lock torque allocation for each wheel, so as to determine the target torque increment for each wheel based on the weighted virtual differential lock torque allocation and torque vector allocation.

8. An electronic device, characterized in that, Including memory and processor; The memory is used to store computer programs; The processor is configured to implement the torque distribution method as described in any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, implements the torque distribution method as described in any one of claims 1 to 6.

Images